Let AI triage resumes before human review
Recruiters used AI to condense applications, filter obvious misses, and leave the final shortlist for a person.
- What they did
- Commenters said they used AI in a fairly hands-on way: it turned resumes into short summaries, helped with sourcing queries, and cut down piles of clearly unsuitable applicants. One recruiter described a custom-built workflow that pulled screening details from the page, passed them into a local Ollama qwen3:8b model, and then skipped past poor matches so only a narrowed list remained for manual review.
- How it went
- The overall reaction in the thread was divided. Some recruiters said AI still does a weak job on resumes, and one AI phone-screen experiment at a company did not work out; the clearest win mentioned was the local filtering setup, which was said to leave about 90% good fits among the candidates it separated.
- Tips
- Use this kind of agent to remove noise, not to make hiring decisions on its own. Keep a person involved at the end, especially before any rejection or outreach.
Try it yourself with Claude Cowork
Look through the resumes in [folder or inbox] for the open [job title]. For each person, produce a brief summary, list the most relevant skills and experience, and score how well they line up with [must-have criteria] and [bonus criteria]. Put the strongest matches first and explain any borderline cases. Pause and ask me before you send, reject, delete, or submit anything. Save the finished table as [file name].
Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.
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